Behavioural Finance at Barclays: An Interview with Greg B. Davies

Mon, 18 Feb 2013 05:11:00 GMT

Last month I was fortunate enough to meet and interview Dr Greg B. Davies, who first set up and now runs Barclays Bank Behavioural Finance unit, the first such unit in a major bank. Rather like Richard Peterson, the subject of a previous interview, Dr Davies approaches his subject from a truly interdisciplinary perspective. Prior to his work with Barclays, he studied economics, philosophy and finance at the University of Cape Town before completing a Masters Degree in Economics at Cambridge where he also received a PhD in Decision Theory and Behavioural Finance. Besides acting as a consultant on cognitive psychology, behavioural economics, behavioural finance, and decision science, he has lectured in Decision Science at the London School of Economics, was an Honarary Research Fellow at University College London and is presently an Associate Fellow at Said Business School at Oxford University.

In this extended interview Dr Davies talks about his academic background, how that came to be applied in his work for Barclays and his musical collaboration with composer, Alexis Kirke, Open Outcry.

MoneyScience -Thank you for joining us Greg. First of all I thought it might be interesting to talk a little bit about your academic background and how you initially formed an interest in Behavioural Finance.

Greg Davies - To be honest, it was almost completely by accident. I started life studying economics and philosophy and in particular the philosophical underpinnings of economics always interested me a great deal. So, many years later when I had made the decision to go and do a PhD I was actually initially focussed on doing a PhD in pure philosophy. I was going to be studying the philosophy of rationality. I wanted to do a PhD purely because I was passionately interested about the subject, it was never intended to be a career move in any way whatsoever, except possibly into academia. But, as I started reading around the topic of the philosophy of rationality to put together a proposal, I started stumbling across this aspect of the field that I’d never come across before which was; I knew about the rational underpinnings to economic theory, I knew about some of the philosophy of rationality, but I’d not come across any of the behavioural psychology elements and the experimental elements and this just seemed to me to be absolutely the way forward. Suddenly here was something that wasn’t just looking at the philosophical underpinnings but was testing these and asking how do people actually do it? A scientific methodology wedded to some of the deep decision theory in philosophy. It also seemed to me to take on board some of the more practical aspects. By this stage I’d already worked many years as a management consultant, I had some commercial background and this seemed a way to steer my PhD into something that wasn’t purely Ivory Tower, but actually brought in some of my practical finance background and experience. So, suddenly I stumbled across what was effectively behavioural finance and behavioural economics. And quickly swung my PhD proposal in that direction, moved my application from a philosophy department back to an economics department, and that was shortly before Daniel Kahneman won his Nobel prize so it was at the time really still the lunatic fringe of the economics faculty but shortly thereafter took off in respectability and popularity.

MS - So your timing was good!

GD – Yes though I have to say through no foresight or prescience on my part. Serendipity!

MS – You’ve had over a decade of experience in this field now but were there many people at that early stage doing similar work that you were aware of?

GD – There were but those in the UK were fairly isolated. Before then, the only places with academic programs in Behavioural Finance were really in the United States. There were people in the UK that were heading in that direction but they tended to be fairly isolated. Certainly in the economics faculty in Cambridge, where I was, I was the only one doing anything close to that. I did forge links with a number of academics in different universities and departments who were starting to combine these ideas. Most notably in LSE philosophy department, Warwick University cognitive psychology department, and there were a few others but it was certainly very exploratory at that stage still. Which is interesting if you think about it now because it was not that long ago, and there are now dozens of Masters courses in behavioural finance, behavioural psychology, behavioural this that and the other and it’s wonderful that’s happened in a very short space of time.

MS – So from its beginnings as an interdisciplinary area the subject has become a field in its own right?

GD – Absolutely. And some of the challenges back then were more of translation than anything else. You had psychologists and economists working on the same problems, completely independently, talking about the same topics using quite different languages and I used to find myself going to psychology conferences where I would be considered to be hopelessly economic and economics conferences where I was considered to be hopelessly psychological and behavioural, and a large part of what I spent my time doing there was translating these two tribes to each other because actually they were thinking about very similar issues often in very similar ways both with fairly quantitative mathematical models and foundations underpinning them, and both ultimately resting on a critique of Expected Utility Theory. But they were frequently using quite different languages to express the same directional thoughts.

MS – So that process of becoming a discipline means that the language has now become standardised?

GD – It has to an extent. The economic foundations came out of the questions of how do we take expected utility theory and amend it, so it was all model driven. The psychological approach was much more experimental, let’s take a hundred people, split them into two groups and see how they make different decisions, which of course had implications for expected utility theory but the psychologists didn’t start from the theory and work towards the reality, they did it backwards. And many times this is what was happening – you had economists working from theory and incorporating experimental evidence and psychologists starting from experimental evidence and gradually moving towards theory… and not always meeting in the middle.

MS – Following on from your PhD, you have done some teaching among other things. How did it come about that you came to Barclays?

GD- My intention on finishing my PhD was not to go into pure academia. The reason for that was that during my PhD I had helped some guys at Warwick University; Professor Nick Chaser who was head of cognitive psychology there at the time, and one of his PhD students who had in fact left the same management consultancy I used to work for at the same time to do a PhD in very similar things, with Nick, and I’d helped these two set up a boutique consultancy start-up called Decision Technology which was entirely aimed at transferring ideas from academic decision scientists to the real world, so throughout my PhD I was maintaining an interest in how we can turn these ideas from theory into practice. When I finished the PhD I continued to do that. I had an honorary research scholarship at UCL which allowed me to keep a toe firmly in the academic world but didn’t require me to be a fully paid-up member of academia: in short they didn’t pay me to do anything and I wasn’t really required to do anything, it was an affiliation more than anything else, and at the same time was working with Decision Technology in a consulting way. The idea was to maintain this 50/50 split so I could fund my academic interests and pursuits through consulting work. In reality that was a very difficult tightrope to walk, it’s extremely difficult to make it work in practice unless you are the most disciplined individual in the known universe because when the consulting work isn’t there you have no income and you’ll spend more than your dedicated 50% looking for the consulting jobs. When the consulting work is there, it has deadlines that bear no relation to the sort of deadlines you face in the academic world and of course you spend more than your 50% of time meeting those deadlines. So actually, that was great, I learnt an enormous amount from it but wasn’t really suiting my goals of being able to maintain this dual lifestyle of practical and theoretical.

We were also at the time trying to sell projects into the banking industry on behavioural finance because this was really what my PhD was focussed very much on: psychology of risk and uncertainty, and financial decision making. What we were doing as a consultancy was much more in consumer behaviour. Whilst that was fascinating I wanted to get back to the quantitative finance side of behavioural science. And so, we were trying to sell these projects to banks and meeting with polite interest, I think, until completely out of the blue, and this wasn’t on a basis of any tendrils I was putting out, I got a call from Barclays to say – it seemed that this idea had come up completely independently – we are thinking of seeing if this behavioural finance thing has any practical uses in the finance industry would you come in and talk to us about it. And so it led on from there. They proceeded to describe to me some fairly high level ideas about introducing behavioural finance into the banking industry which really were completely in the sweet spot of what I wanted to do, a mix of doing it quantitatively integrating with classical finance theory by bringing really robust behavioural techniques into play. That was just over 6 years ago now and since then I’ve been with Barclays. The great thing about Barclays is that I really do get to do a number of things; we do primary research, we implement it practically, I get to talk about it a lot but we also get to roll up our sleeves and do data analysis and get on with the geeky stuff.

MS – You mentioned that you were met with polite interest in your original enquiries; does this mean that Barclays were taking a risk in setting up this department; was it an experiment?

GD- It was a risk. Possibly an experiment, to be honest, I don’t think anyone really knew that it was going to work. So in that sense I think yes it was an experiment. They were in many senses quite prescient at the time, it was starting to become popular in 2006 (you know we had the burst from the Nobel prize in 2002); there had been a raft of popular science books exploring these areas like the Malcolm Gladwell’s and various other popular science books. I think Barclays Wealth, as it was at the time, was looking for new ideas to make a change in the industry. This was one of the things that they came across and they thought well let’s take a chance on it.

MS – Since you’ve set this group up there have been others formed, and Barclays have demonstrated that the model was workable and useful, but is the model still relatively rare?

GD- Absolutely, though I have to say, the other groups aren’t exactly following our model. All of the other behavioural finance groups that I know of in banks are taking slightly different angles on it. And I think that’s because we don’t know that there’s one model to do this yet. We’ve been doing it for 6 years and we’re still scratching the surface of what is potentially possible in behavioural finance. Other groups particularly in the United States in banks and organisations have started forming teams on behavioural finance. It’s still definitely the exception rather than the norm and those teams have only really started to form in the last 2 years. But there are other types of organisation looking at this. There are an increasing number of small consulting companies that are bringing various aspects of psychology into their consulting work. There are government institutions that are looking into it, so we have a large unit here in the UK – the so-called ‘Nudge Unit’, and Cass Sunstein has been advising the US government on similar issues. The FSA for instance has an interest in behavioural finance and how that can be useful, and NEST – National Employment Savings Trust – is very interested in behavioural finance… so there are a lot of different groups starting to kick off in small ways, but I’d say for the most part it’s still a bit of a try-it-and-see approach.

MS – You’ve identified three aspects of your group’s work at Barclays, first of all Barclays Global Investment Philosophy, then the application of Behavioural Methods to Quantitative Asset Allocation, and then Personality Profiling as a discipline and its application. How has the work you’ve been doing impacted materially on the business?

GD – When we started it was quite exploratory, and I definitely wanted to do something practical, to create tools that would make this useful to Barclays as an organisation rather than just come in there and talk about it. Behavioural Finance is really easy to talk about. There are lots of ready-made examples in dozens of books that are quirky and interesting and cute anecdotes. Which is funny given that one of the primary findings of Behavioural Finance is that, in fact, mere self-knowledge and education are very seldom enough to actually change behaviour. You need to do something more real. So what we thought we needed to build tools that can go into the workstations, the desktops, into the hands of our private bankers and indeed other functions around the bank that will mean that the sort of ideas we are having can be used practically by a large range of people that are not themselves necessarily specialists in behavioural finance. That requires a lot of IT development, it requires plugging these things into your IT systems, it requires plugging the ideas into your sales processes , doing a great deal of internal training, building it into your marketing material a lot of things that are much more about practical business than necessarily are about esoteric ideas . To make it functional you have to do it from the perspective of the business and you have to sell it into the business and to the external world in that regard.

The three pieces that you talk of there – we started with the profiling. The obvious place for behavioural finance in wealth management was to ask, how do we get to know our individual clients better – their needs, and how they respond to the investment journey? If we can know them better we can provide them with more tailored solutions which will make them more comfortable with you on the investment journey it seeks to serve their emotional needs as well as their financial needs. And by increasing the amount of comfort you actually reduce people’s initial knee-jerk emotional responses and, ironically, by stepping slightly away from the ‘rational’ theoretical solution you might actually get people better returns. If you make people comfortable they are less likely to make mistakes and they will do better. So that profiling is key, and first thing we did there was to design our financial personality assessment psychometric tool. It took us a year to build it. We used data from over 3000 people around the world with very robust psychometrical techniques underpinning it. That enables every one of our personal bankers around the world to give a 5-6 minute psychometric test to their clients that will give us an objective starting point to say: how are you different from the last client to walk in the door and what should we change as a result? The quantitative side is much more about saying well, how do we change the result? The industry for decades has relied on portfolio optimization theories that were originated in the 1950s. There is nothing wrong with those; they are still the right answer under the assumption that you are a completely rational individual in the sense of Homo economicus. Unfortunately none of us are. So what we’ve been trying to do is in a much more quantitative sense say how do we change the portfolio optimization model to take account of what we now know from behavioural science to be differences in the way people perceive risk; to be differences not just in the way we trade-off risk and return but how we trade off both risk and return in the long term against our need for emotional comfort in the short term. These are things we can start to create increasingly robust measures of. This is not to say that we can provide the right solution to 4 decimal places. But it does mean that if we have two individuals in front of us both of whom have the same degree of risk tolerance, in classical finance they get the same solution. But one of those may be very emotionally engaged with the short term and the other may be relatively blasé and relaxed about it. Those two people should have different portfolios even if the risk/return trade-off they are seeking in the long term is the same. The investment philosophy is really how we draw all of this together. So our investment philosophy is: how do we ascertain everything we need to know about clients on the one hand with regard to their financial situation as well as their personality and emotional situation, and tie it to the optimal solution that we can provide for them with the full knowledge of our product set, our portfolio allocations etcetera. So it really is a mix of understanding clients as individuals, trying to improve classical quantitative models to make better use of our financial knowledge and the philosophy of how we draw all that together and then provide that to the bankers to do that for all our clients around the world.

MS – To what extent can the interpretation of this profiling be classed as a science rather than an art?

GD - You can use the science to fairly accurately get to a set of questions that you know are going to lead you to a measure of an individual personality on a dimension that is stable and discriminating. That we spent 2007 doing; and most of the rest of the 6 years since we have been refining what we do with those scales. Classical theory only has space for one of them: long term risk tolerance. The other 5 scales are much more about emotional responses to the journey. And that’s really been where a lot of our research and learning along the path has been. It becomes a mix of art and science, but we have spent 5 years collecting data to support the science part. We’ve been – difficult to use the word fortunate – but the fact that those five years have been in a period of extreme financial dislocation and turmoil actually gave us the opportunity to stress test, to kick the tyres of what we were doing, much faster. It’s been an important learning ground to have had the slightly strange luck of doing this for the first time in a period of extreme turmoil because you learn faster that way. If we had started at the beginning of a long bull run we just might not have learnt anything near as fast as we have.

So you’re absolutely right, it’s connecting those personality scales to the solution that we offer that we spent a lot of time tightening up. And now for example what we do is score our entire product set, not just on its asset allocation and its level of risk, but on a number of secondary characteristics… how much smoothing of the short term journey does the product provide? Is it more active or passive in its management style? These are things that we now know we can reliably attribute to personality scales. Certain personality types have preferences for characteristics of a portfolio that go well beyond standard risk/return trade offs.

The fundamental question for us is not ‘How do I eliminate my need for emotional comfort?’, which is pretty much what classic finance assumes – it says ‘needing emotional comfort in the short term is simply stupid and irrational don’t do it. We’ve told you what the right answer is. If you fail to carry that through that’s your problem’. That’s pretty much what the industry has done for the last 50 years. Here’s the right answer, and we’ve got to conform. ‘We’ve got 20 maths PhDs holed up in a darkened room back there, and they’ve come up with the right answer. Now you just need to follow through with it’.

We can’t ignore our need for emotional comfort as a human; the question is not how we eliminate it, it’s how we satisfy our need for emotional comfort as cheaply and efficiently as possible because if we don’t plan for emotional comfort or if you like, purchase emotional insurance, in setting up a portfolio, we’re going to seek it at times of stress in an unplanned and a very expensive way. This is where all the buying high selling low, overtrading, and action bias come in. All these biases can really be seen as me, as an investor, deviating from what the right decision is in order to acquire the emotional comfort I severely crave right now. We need it, the question is can we get it to you more efficiently?

MS - So now the field has become established, what do you feel are the big challenges facing behavioural finance in banking going forward?

GD- There are so many. I’ve said we are just scratching the surface, but we’ve started from the wealth management position because that’s where it makes sense to start looking at individuals’ investment behaviour, because you’ve got individuals who have a lot of money. As a result we’ve looked at investment as our primary goal and asked ‘how do we improve people’s investing behaviour?’ If you look more generally, however, you can only invest once you’ve got money to invest so all the issues about savings versus expenditure in the retail market become important - issues about pensions, and how to approach the decumulation phase from a behavioural perspective - these are things that need a lot of attention and which we have started putting attention on. We spend a lot of time advising individual clients on how they should think about using their portfolios and their investment decision making. We also do that internally looking at our own portfolio managers because of course they are also making investment decisions. So there’s a whole raft of things you can do to improve the decision making of fund managers, portfolio managers, traders etcetera.

One of the things I’m more sceptical about - and this is where there are a lot of people dabbling with behavioural finance to various degrees of intensity on the other side of the coin - it’s not ‘how do I help people make better decisions as investors or traders?’, it’s ‘how do I use this knowledge to take advantage of the market’s irrationality?’ So there are a lot of fund managers out there who are in various ways using behavioural ideas to try and beat the market or to try and take advantage of the mass irrationality of the market. This is interesting but it’s really not the low-hanging fruit. Firstly it’s by no means clear that our improved knowledge of individuals and individual psychology really enables us to aggregate that up to a better predictive model of the market except in the simplest of ways. It’s like taking Newtonian mechanics and trying to use it to describe fluid dynamics. You hit chaos, you hit emerging properties of the system that cannot be described by an understanding of the atomic elements. The same is true in markets. You have incredible complexity there and the fact that we know how individuals are biased in 79 different ways (or however many it is) really doesn’t enable us to predict the future.

We can say predictive things like… there will always be cycles; there will always be a crash at some point. Whether, beyond the use of fairly simple momentum modelling type strategies we can really use this to out-perform the market is I think open to question. Certainly I believe it’s possible but, as I say, that’s not where the low-hanging fruit is. You could pour millions and millions of dollars into trying to build a system based on behavioural finance that tries to beat the market. Other people will be doing the same. You enter an arms race and if you’re the best, you may eke out maybe 10 basis points a year. If I can help an individual client make better individual decisions 10 basis points is neither here nor there, you can save people 3-5% a year. So, the low-hanging fruit for me is using behavioural finance to improve financial decision making - not to try and beat the market.

MS – What do you make of Sentiment Analysis and the buzz around that?

GD – Well if we are using it to do that I think there are certain elements which are promising. One is the use of natural language processing and computational linguistics to look at real-time granular text feeds from twitter, blogs, newspaper reports etcetera to try and create very granular and immediate sentiment indicators and I think that is a data set that is complex to use but I think that’s where an inherently behavioural technique might be useful. That would be interesting to explore. Another area is Network Theory and agent based modelling. These are things that start to bring something of our knowledge of individuals but don’t just say that we can aggregate up the disposition effect and assume that the market as a whole exhibits it. I’ve just finished Paul Ormerod’s book on Positive Linking where he’s trying to do exactly this, describe the linkages between improved behavioural models but put it into a network context that is inherently potentially chaotic and unpredictable. Markets are unpredictable and in some deep sense probably always will be unpredictable. It’s not a case of if we improve our knowledge about the psychological makeup of the individual traders in that market that we will necessarily somehow overcome that predictability threshold. Because of network structure of the markets themselves that threshold has nothing to do with our level of knowledge of individual psychology.

MS – That interdisciplinary aspect of Behavioural Finance continues then, in the tools you can bring in to implement the approach. I am interested in that connection between Behavioural Finance and Quantitative Finance. It’s only in the last few years I've heard the term Quantitative Behaviour Finance as a sub-discipline. Could you elaborate on the quantitative aspects of behavioural finance?

GD – I am sometimes puzzled by the perception that Behavioural Finance is not quantitative. If you look at most of the early academic work on this - in fact most of the academic work full stop - it starts from testing very quantitative models of expected utility theory. The feel of the decision theory of non-expected utility theory is as mathematical and quantitative as you could possibly hope to be, and that’s what underpins most of this. Its simply because the popularisation of behavioural finance has drawn on anecdotes to illustrate the sort of biases that people exhibit that the popular perception is that it is actually all about anecdotes and parlour gags and cute stories. But if you look at the paper that essentially was the chief foundation of Kahneman’s Nobel prize, the model of prospect theory , it is a quantitative paper. Amos Tversky (Kahneman’s long time collaborator and co-author) was a mathematician and a very deep thinker about the axiomatic approach to measurement science. There is nothing un-quantitative about the academic background to behavioural finance whatsoever. In fact, quite the opposite.

However it is true that most of the commercial application has tended to be along the lines of: here’s a bunch of biases; we can tell nice stories about them lets figure out how to tell the stories in a way we can make people do something different. For us at Barclays it’s always been about rigour. So I think you’re right, in one aspect it is data. Data really enable us to drive into individual behaviour in a way we’ve never been able to before. Our computing power and the data we’ve got available is wonderful. One of the recent developments in behavioural finance is to look more strongly at individual differences. A lot of the early work was on how people on average exhibit loss aversion, or whatever it may be. Now we ask, “how do individual differences in personality make people differentially susceptible to each of these biases and how do they express themselves differently in different places.”

There’s a lot of data analysis to get into with that, but another part of it is taking the normative models of quantitative finance and understanding that these models give the right answer only under certain mathematical assumptions of what rational is. Once we relax those assumptions and we have a more broad thinking definition of rationality we can start to still have quantitative models that are behaviourally driven.

The book we published last year Behavioural Investment Management is entirely quantitative. It’s taking modern portfolio theory and saying well: Markowitz made some assumptions in there about human behaviour…most notably that people care only about the mean and variance of distributions. Now we know that to be untrue. When Markowitz was creating that theory it was in a world where we didn’t have much computing power – computers took up whole rooms at that time – and we didn’t have the behavioural knowledge that we have today.

So our book is asking how we can build portfolio theory from a platform that is more robustly underpinned by the model of human decision making. It requires looking at the utility function more carefully, but it’s all mathematical, all quantitative, all modelled. A number of people were quite surprised by that – “I thought this was going to be a book about behavioural science but there are equations throughout it”. Well, yes, actually I think to really make behavioural finance work in practice in the industry you have to talk the language of the industry. You have to do it quantitatively, you have to explain why these assumptions that you’re questioning are wrong and what you would replace them with. A lot of the popularisation of behavioural finance has been quite combative, you know ‘in the red corner is behavioural finance, in the blue corner is classical finance’, you have to choose – one of them will win! We talk a lot more about behaviouralising finance. Use the classical models, use quantitative foundations, but figure out how we humanise them. How do you relax the assumptions, how do you push them out to be more appropriate to real people rather than just the right answer for Homo economicus?

MS – This is out of your specific area of interest but I would like to hear your view on it. Allegations have been made in the last few years that major banks were using their data to target vulnerable people who were, for example, paying the minimum mount on their credit cards in order to offer them more credit. Are banks actually targeting people in this way and, if so, are the techniques used drawn from a behavioural model or is that simply a data-mining exercise?

GD – Any technique or tool that tells us something about human behaviour can be used for good or bad. Arguably a lot of the findings of behavioural economics and behavioural psychology are of things that the marketing industry has discovered through a trial and error approach over the last hundred years already and marketing is about trying to induce people to make the decision we want them to make. It’s about analysing their behaviour and there’s a lot behind that. They become increasingly sophisticated at doing that. One of the underpinning justifications for the nudge approach at an experimental level is that people are being influenced behaviourally anyway and we should be able to use that to influence them for good as well as for bad. To be honest I know of no intentional uses of this in a manipulative way in banking. I consider myself to be very fortunate because the role I have here and the mandate I have at Barclays is very definitely to ask the question: what is the right answer for our clients and how do we help get them there? Of course it could be possible that there are, or will be, behavioural teams that are hired to follow a slightly different mandate, but for us the starting point is always: what is the best investment decision and how do we help people to get to that? Because we are tied in to our investment strategy teams, into the quantitative optimisation teams, we are interested in improving returns for our customers and helping them get to the best place - which is great and we think about that very carefully. That’s not to say that there has to be a zero sum game. I think the real point about this is doing the right thing for your clients in the long term and helping your clients get a better investment returns and be more comfortable with their investment is not a zero sum game for banks and by doing that we get clients that are more satisfied, clients with higher returns, clients who are likely to have lower attrition rates, clients who are likely to bring us more referrals.

The popular conception that by trying to use behavioural finance to do the right thing for clients in the long term must be harmful for the banks I think is a misconception. That’s where the value comes from and that’s very much the approach that we take. Clearly there are more rapacious uses of behavioural finance. Most of those that I know of, that are being used openly, are not trying to manipulate decision making. They are trying to make use of irrationality in the markets to outperform the markets. So yes, it’s certainly possible that these techniques could be used for purposes that are not to the greater good but, emphatically, that’s not how we do things here in Barclays.

MS – I was very interested in your Open Outcry project with composer Alexis Kirke. Could you tell us a little bit about that and how it came about?

GD - Absolutely. I got approached out of the blue by Alexis several years ago. He was looking for someone in finance who would advise him on this project he was starting to undertake. He has a background in quantitative finance but he is a composer who specialises in computer music, quite experimental stuff. He had this idea that resonated so strongly with me because in these open outcry trading pits (of which there are increasingly few) - there is noise, there is emotion and this is an audible and visual expression of people’s behaviour and emotions in pursuit of a financial goal.

He said: I’m fascinated by what would happen if you could harness that and turn the market into something that was also an artistic work, an expression of that energy. So we worked together (though the idea was very much originally his) and collaborated to create this market. I designed a quantitative system that was a stochastic model of three different assets and we had 12 traders who were buying and selling these assets as the market moved on big screens in the background.

The traders most of the time could only trade by singing their trades, and so Alexis composed 6 phrases for buying and selling of each of the three assets. When two traders matched on a buy and sell the harmonies locked in very closely together and the phrases were designed so that when more people were buying and the markets were rising it would be quite harmonious, but if everyone was selling at the same time there would be an extraordinary amount of disharmony.

We designed all this; then we took 12 singers and trained them to be traders. And the most amazing thing about this is in the end the singers were not really the performers. They were more the instruments. It was the market that was the performer, because the singers weren’t trying to be musical. They were trying to earn money. The audience was sitting in the middle of this ring of singers, who were trading. We had very little control once we set this in motion we didn’t know what was going to happen but what you heard in the middle was a musical expression of a functioning market.

To me this was artistic and musical, and it had a lot of parallels with what academic behavioural economists do to study market structure. They set up experimental markets and they manipulate the structure to see what happens. So we had that experimental element, but also an expression of the individual emotions and behaviour of the traders singing in aggregate coming out of that. It was a wonderful evening, we had Marcus du Sautoy speaking about chaos and how maths expresses itself in theatre and in art. We had Carl Richards of Behavior Gap fame, who was exhibiting his sketches and artworks there. It was an absolutely fascinating evening.

One of the reasons this resonated so much with me is that since I was a young boy I’ve always been a singer. I still sing and I’m very involved in music wherever possible, and it was the most extraordinary opportunity to bring together two sides of my life that I never thought would work in parallel in any way whatsoever. It’s interesting; we’re starting to think of ways to do other similar things, ways of taking financial concepts and expressing them artistically. So watch this space…

MS - Thank you very much for your time, Greg. I'll look forward to talking with you in the future.